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The adaptability of the classical top-k frequent item sets mining algorithms is unsatisfied when being applied to some large datasets with both large scales of transactions and items. In this work, an algorithm called SIBA (sampling, improved bat algorithm (BA)) is proposed to solve this problem. SIBA applies BA and improves it by cloud model to search frequent item sets from a large number of items...
Multi-population-based bio-inspired computation may use migration among groups to increase the search diversity. Through good solutions exchanged among sub-populations, better solutions may be found with a high probability. In this paper, we propose two algorithms to dynamically adjust the two primary parameters, migration interval and migration rate, for flexibly reflect solution situation for effective...
The problem of scheduling independent users' jobs to resources in Grid Computing systems is of paramount importance. This problem is known to be NP-hard, and many techniques have been proposed to solve it, such as heuristics, genetic algorithms (GA), and, more recently, particle swarm optimization (PSO). This article aims to use PSO to solve grid scheduling problems, and compare it with other techniques...
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